Systems And Methods For Voice Assisted Goods Delivery

ABSTRACT

The following relates generally to voice assisted delivery of goods. In some embodiments, a digital assistant receives audio data, and determines an intent from the audio data. The digital assistant may then match the determined intent to a flow of a set of flows, where the set of flows may include at least one of: (i) requesting curbside pickup of an item, (ii) requesting locker storage of the item, (iii) requesting an indication of locations that the item is available, (iv) requesting an indication of an inventory of a retail store, (v) requesting ads for an additional item that is related to the item, (vi) requesting a status of an order for the item, (vii) requesting drone delivery of the item from a retail store to a residence, or (viii) requesting drone delivery of the item from a warehouse to the residence. The matched flow of the set of flows may then be executed.

BACKGROUND

Often, a purchaser of a product will order the product online using asmartphone, tablet, personal computer, or other computing device. Yet,using these devices may sometimes be burdensome. For instance, a user ofthe device (e.g., a user who is purchasing an item) may not readily beable to type into the device. For example, it may be difficult for theuser to use the smartphone because of a physical or medical condition(e.g., the user has broken wrists or fingers, making typing on thesmartphone or other device difficult). In another example, it may bedifficult or dangerous for a user to type into a smartphone because theuser is driving a vehicle.

The systems and methods disclosed herein provide solutions to theseproblems and others.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter.

In one aspect, there is a computer computer-implemented method for voiceassisted delivery of goods. The method may comprise determining anintent from digital data, wherein the digital data comprises audio dataor text message data. The method may further comprise matching thedetermined intent to a flow of a set of flows, wherein the set of flowsincludes at least one of (i) requesting curbside pickup of an item, (ii)requesting locker storage of the item, (iii) requesting an indication oflocations that the item is available, (iv) requesting an indication ofan inventory of a retail store, (v) requesting ads for an additionalitem that is related to the item, (vi) requesting a status of an orderfor the item, (vii) requesting drone delivery of the item from a retailstore to a residence, or (viii) requesting drone delivery of the itemfrom a warehouse to the residence. The method may still further compriseexecuting the matched flow of the set of flows.

In another aspect, there is a computer system for voice assisteddelivery of goods. The computer system may include one or moreprocessors configured to determine an intent from digital data, whereinthe digital data comprises audio data or text message data. The one ormore processors may be further configured to match the determined intentto a flow of a set of flows, wherein the set of flows includes at leastone of: (i) requesting curbside pickup of an item, (ii) requestinglocker storage of the item, (iii) requesting an indication of locationsthat the item is available, (iv) requesting an indication of aninventory of a retail store, (v) requesting ads for an additional itemthat is related to the item, (vi) requesting a status of an order forthe item, (vii) requesting drone delivery of the item from a retailstore to a residence, or (viii) requesting drone delivery of the itemfrom a warehouse to the residence. The one or more processors may befurther configured to execute the matched flow of the set of flows.

In yet another aspect, there is a computer system for voice assisteddelivery of goods. The computer system may include one or moreprocessors; and a program memory coupled to the one or more processorsand storing executable instructions that, when executed by the one ormore processors, cause the computer system to determine an intent fromaudio data. The instructions may further cause the computer system tomatch the determined intent to a flow of a set of flows, wherein the setof flows includes at least one of: (i) requesting curbside pickup of anitem, (ii) requesting locker storage of the item, (iii) requesting anindication of locations that the item is available, (iv) requesting anindication of an inventory of a retail store, (v) requesting ads for anadditional item that is related to the item, (vi) requesting a status ofan order for the item, (vii) requesting drone delivery of the item froma retail store to a residence, or (viii) requesting drone delivery ofthe item from a warehouse to the residence. The instructions may furthercause the system to execute the matched flow of the set of flows.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a platform configured for delivery of goods inaccordance with various embodiments disclosed herein.

FIG. 2 shows an overview flowchart of an example implementation.

FIG. 3 shows a flowchart of an example implementation of a process,including an intent being determined by a digital assistant.

FIG. 4 shows an example implementation of a process, including audiodata being sent to an audio analyzer to determine an intent.

Advantages will become more apparent to those skilled in the art fromthe following description of the preferred embodiments which have beenshown and described by way of illustration. As will be realized, thepresent embodiments may be capable of other and different embodiments,and their details are capable of modification in various respects.Accordingly, the drawings and description are to be regarded asillustrative in nature and not as restrictive.

DETAILED DESCRIPTION

The present embodiments relate to, inter alia, voice assisted deliveryof goods. In this regard, one objective of the present application is toprovide better or easier access to goods delivery. For instance, a usermay wish to purchase goods, but be in a situation where it is difficultfor the user to type into her smartphone. In such a situation, the usermay prefer to purchase the goods via voice assistance. Alternatively,even if the user is not in a situation where it is particularlydifficult to type into a device, the user may still prefer to purchasethe goods via voice techniques for convenience or personal preference.To this end, some embodiments enable a simple plug and play platformthat provides easy purchasing or delivery options.

Exemplary Infrastructure

FIG. 1 illustrates a platform 100 configured for voice assisted goodsdelivery in accordance with various embodiments disclosed herein. In theexample embodiment of FIG. 1, the platform 100 includes merchant 101(e.g., a first entity). The merchant 101 may be any merchant, such as amerchant that sells goods or products. In the example of FIG. 1,merchant 101 includes server(s) 102, which may comprise one or morecomputer servers. In various embodiments, server(s) 102 comprisemultiple servers, which may comprise multiple, redundant, or replicatedservers as part of a server farm. In still further embodiments,server(s) 102 are implemented as cloud-based servers. For example,server(s) 102 may comprise a cloud-based platform such as MICROSOFTAZURE, AMAZON AWS, or the like.

Server(s) 102 may include one or more processor(s) 104 as well as one ormore computer memories 106. The memories 106 may include one or moreforms of volatile and/or non-volatile, fixed and/or removable memory,such as read-only memory (ROM), electronic programmable read-only memory(EPROM), random access memory (RAM), erasable electronic programmableread-only memory (EEPROM), and/or other hard drives, flash memory,MicroSD cards, and others. The memories 106 may store an operatingsystem (OS) (e.g., Microsoft Windows, Linux, Unix, etc.) capable offacilitating the functionalities, apps, methods, or other software asdiscussed herein. The memories 106 may also store machine readableinstructions, including any of one or more application(s), one or moresoftware component(s), and/or one or more application programminginterfaces (APIs), which may be implemented to facilitate or perform thefeatures, functions, or other disclosure described herein, such as anymethods, processes, elements or limitations, as illustrated, depicted,or described for the various flowcharts, illustrations, diagrams,figures, and/or other disclosure herein. For example, at least some ofthe applications, software components, or APIs may be, include,otherwise be part of, a machine learning component. It should beappreciated that one or more other applications may be envisioned andthat are executed by the processor(s) 104.

The processor(s) 104 may be connected to the memories 106 via a computerbus responsible for transmitting electronic data, data packets, orotherwise electronic signals to and from the processor(s) 104 andmemories 106 in order to implement or perform the machine readableinstructions, methods, processes, elements or limitations, asillustrated, depicted, or described for the various flowcharts,illustrations, diagrams, figures, and/or other disclosure herein.

The processor(s) 104 may interface with the memory 106 via the computerbus to execute the operating system (OS). The processor(s) 104 may alsointerface with the memory 106 via the computer bus to create, read,update, delete, or otherwise access or interact with the data stored inthe memories 106 and/or the database 105 (e.g., a relational database,such as Oracle, DB2, MySQL, or a NoSQL based database, such as MongoDB).The data stored in the memories 106 and/or the database 105 may includeall or part of any of the data or information described herein,including, for example, the one or more search requests, the one or moretransaction details, and the profile information of the user.

The server(s) 102 may further include a communication componentconfigured to communicate (e.g., send and receive) data via one or moreexternal/network port(s) to one or more networks or local terminals,such as computer network 120 and/or terminal 109 (for rendering orvisualizing) as described herein. In some embodiments, server(s) 102 mayinclude a client-server platform technology such as ASP.NET, Java J2EE,Ruby on Rails, Node.js, a web service or online API, responsive forreceiving and responding to electronic requests. The server(s) 102 mayimplement the client-server platform technology that may interact, viathe computer bus, with the memories(s) 106 (including theapplications(s), component(s), API(s), data, etc. stored therein) and/ordatabase 105 to implement or perform the machine readable instructions,methods, processes, elements or limitations, as illustrated, depicted,or described for the various flowcharts, illustrations, diagrams,figures, and/or other disclosure herein. According to some embodiments,the server(s) 102 may include, or interact with, one or moretransceivers (e.g., WWAN, WLAN, and/or WPAN transceivers) functioning inaccordance with IEEE standards, 3GPP standards, 4G standards, 5Gstandards or other standards, and that may be used in receipt andtransmission of data via external/network ports connected to computernetwork 120.

Server(s) 102 may further include or implement an operator interfaceconfigured to present information to an administrator or operator and/orreceive inputs from the administrator or operator. As shown in FIG. 1,an operator interface may provide a display screen (e.g., via terminal109). Server(s) 102 may also provide I/O components (e.g., ports,capacitive or resistive touch sensitive input panels, keys, buttons,lights, LEDs), which may be directly accessible via or attached toserver(s) 102 or may be indirectly accessible via or attached toterminal 109. According to some embodiments, an administrator oroperator may access the server(s) 102 via terminal 109 to reviewinformation, make changes, input training data, and/or perform otherfunctions.

As described above herein, in some embodiments, server(s) 102 mayperform the functionalities as discussed herein as part of a “cloud”network or may otherwise communicate with other hardware or softwarecomponents within the cloud to send, retrieve, or otherwise analyze dataor information described herein. Furthermore, server(s) 102 and/or theirrespective memorie(s) 106 are configured to store data including forexample, goods data, inventory data, customer history data, patientdata, pharmacy data, prescription data, and so forth.

In general, a computer program or computer based product, orapplication, in accordance with some embodiments may include a computerusable storage medium, or tangible, non-transitory computer-readablemedium (e.g., standard random access memory (RAM), an optical disc, auniversal serial bus (USB) drive, or the like) having computer-readableprogram code or computer instructions embodied therein, wherein thecomputer-readable program code or computer instructions may be installedon or otherwise adapted to be executed by the processor(s) 104 (e.g.,working in connection with the respective operating system in memories106) to facilitate, implement, or perform the machine readableinstructions, methods, processes, elements or limitations, asillustrated, depicted, or described for the various flowcharts,illustrations, diagrams, figures, and/or other disclosure herein. Inthis regard, the program code may be implemented in any desired programlanguage, and may be implemented as machine code, assembly code, bytecode, interpretable source code or the like (e.g., via Golang, Python,C, C++, C #, Objective-C, Java, Scala, Actionscript, Javascript, HTML,CSS, XML, etc.).

The merchant 101 may further include retail store 103 (e.g., a brick andmortar retail store), and/or warehouse 108, which each may have theirown inventory of items.

The example of FIG. 1 further illustrates audio analyzing entity 130(e.g., a second entity). The audio analyzing entity 130 may be anyentity capable of analyzing digital data, such as audio data or textmessage data. In some embodiments, the merchant 101 is a physicallyseparate entity than the audio analyzing entity 130 (e.g., the merchant101 and the audio analyzing entity 130 are of different companies andare located in different geographic locations). Moreover, by separatingthe merchant 101 and the audio analyzing entity 130, data security anddata privacy may be improved. For example, as will be explained below,the audio analyzing entity 130 may receive audio data from mobile device111 m; and, rather than send the entire audio data to the merchant 101,the audio analyzer 130 may send only an intent determined from the audiodata to the merchant 101. Although the example of FIG. 1 is illustratedwith respect to audio data, it should be understood that any digitaldata, such as text message data, may be used in addition to or in placeof the audio data.

In the example of FIG. 1, audio analyzing entity 130 includes server(s)132, which may comprise one or more computer servers. In variousembodiments, server(s) 132 comprise multiple servers, which may comprisemultiple, redundant, or replicated servers as part of a server farm. Instill further embodiments, server(s) 132 are implemented as cloud-basedservers. For example, server(s) 132 may comprise a cloud-based platformsuch as MICROSOFT AZURE, AMAZON AWS, or the like.

Server(s) 132 may include one or more processor(s) 134 as well as one ormore computer memories 136. The memories 136 may include one or moreforms of volatile and/or non-volatile, fixed and/or removable memory,such as read-only memory (ROM), electronic programmable read-only memory(EPROM), random access memory (RAM), erasable electronic programmableread-only memory (EEPROM), and/or other hard drives, flash memory,MicroSD cards, and others. The memories 136 may store an operatingsystem (OS) (e.g., Microsoft Windows, Linux, Unix, etc.) capable offacilitating the functionalities, apps, methods, or other software asdiscussed herein. The memories 136 may also store machine readableinstructions, including any of one or more application(s), one or moresoftware component(s), and/or one or more application programminginterfaces (APIs), which may be implemented to facilitate or perform thefeatures, functions, or other disclosure described herein, such as anymethods, processes, elements or limitations, as illustrated, depicted,or described for the various flowcharts, illustrations, diagrams,figures, and/or other disclosure herein. For example, at least some ofthe applications, software components, or APIs may be, include,otherwise be part of, a machine learning component. It should beappreciated that one or more other applications may be envisioned andthat are executed by the processor(s) 134.

The processor(s) 134 may be connected to the memories 136 via a computerbus responsible for transmitting electronic data, data packets, orotherwise electronic signals to and from the processor(s) 134 andmemories 136 in order to implement or perform the machine readableinstructions, methods, processes, elements or limitations, asillustrated, depicted, or described for the various flowcharts,illustrations, diagrams, figures, and/or other disclosure herein.

The processor(s) 134 may interface with the memory 136 via the computerbus to execute the operating system (OS). The processor(s) 134 may alsointerface with the memory 136 via the computer bus to create, read,update, delete, or otherwise access or interact with the data stored inthe memories 136 and/or the database 135 (e.g., a relational database,such as Oracle, DB2, MySQL, or a NoSQL based database, such as MongoDB).The data stored in the memories 136 and/or the database 135 may includeall or part of any of the data or information described herein,including, for example, the one or more search requests, the one or moretransaction details, and the profile information of the user.

The server(s) 132 may further include a communication componentconfigured to communicate (e.g., send and receive) data via one or moreexternal/network port(s) to one or more networks or local terminals,such as computer network 120 and/or terminal 139 (for rendering orvisualizing) as described herein. In some embodiments, server(s) 132 mayinclude a client-server platform technology such as ASP.NET, Java J2EE,Ruby on Rails, Node.js, a web service or online API, responsive forreceiving and responding to electronic requests. The server(s) 132 mayimplement the client-server platform technology that may interact, viathe computer bus, with the memories(s) 136 (including theapplications(s), component(s), API(s), data, etc. stored therein) and/ordatabase 135 to implement or perform the machine readable instructions,methods, processes, elements or limitations, as illustrated, depicted,or described for the various flowcharts, illustrations, diagrams,figures, and/or other disclosure herein. According to some embodiments,the server(s) 132 may include, or interact with, one or moretransceivers (e.g., WWAN, WLAN, and/or WPAN transceivers) functioning inaccordance with IEEE standards, 3GPP standards, 4G standards, 5Gstandards or other standards, and that may be used in receipt andtransmission of data via external/network ports connected to computernetwork 120.

Server(s) 132 may further include or implement an operator interfaceconfigured to present information to an administrator or operator and/orreceive inputs from the administrator or operator. As shown in FIG. 1,an operator interface may provide a display screen (e.g., via terminal139). Server(s) 132 may also provide I/O components (e.g., ports,capacitive or resistive touch sensitive input panels, keys, buttons,lights, LEDs), which may be directly accessible via or attached toserver(s) 132 or may be indirectly accessible via or attached toterminal 139. According to some embodiments, an administrator oroperator may access the server(s) 132 via terminal 139 to reviewinformation, make changes, input training data, and/or perform otherfunctions.

As described above herein, in some embodiments, server(s) 132 mayperform the functionalities as discussed herein as part of a “cloud”network or may otherwise communicate with other hardware or softwarecomponents within the cloud to send, retrieve, or otherwise analyze dataor information described herein. Furthermore, server(s) 132 and/or theirrespective memorie(s) 136 are configured to store data.

In general, a computer program or computer based product, orapplication, in accordance with some embodiments may include a computerusable storage medium, or tangible, non-transitory computer-readablemedium (e.g., standard random access memory (RAM), an optical disc, auniversal serial bus (USB) drive, or the like) having computer-readableprogram code or computer instructions embodied therein, wherein thecomputer-readable program code or computer instructions may be installedon or otherwise adapted to be executed by the processor(s) 134 (e.g.,working in connection with the respective operating system in memories136) to facilitate, implement, or perform the machine readableinstructions, methods, processes, elements or limitations, asillustrated, depicted, or described for the various flowcharts,illustrations, diagrams, figures, and/or other disclosure herein. Inthis regard, the program code may be implemented in any desired programlanguage, and may be implemented as machine code, assembly code, bytecode, interpretable source code or the like (e.g., via Golang, Python,C, C++, C #, Objective-C, Java, Scala, Actionscript, Javascript, HTML,CSS, XML, etc.).

In the example embodiment of FIG. 1, the merchant 101 and audioanalyzing entity 130 are communicatively connected, via computer network120 and base stations 111 b and 113 b to respective mobile devices 111 mand 113 m. The merchant 101 and audio analyzing entity 130 are furthercommunicatively connected, via computer network 120 and base station 114to car 150. The merchant 101 and audio analyzing entity 130 are stillfurther communicatively connected, via computer network 120 to smartspeaker 155, smart home 160, retail store 180, drone fleet 170, andwarehouse 175. Computer network 120 may comprise a packet based networkoperable to transmit computer data packets among the various devices andservers described herein. For example, computer network 120 may consistof any one or more of Ethernet based network, a private network, a localarea network (LAN), and/or a wide area network (WAN), such as theInternet. In addition, in some embodiments, computer network 120 maycomprise cellular or mobile networks to facilitate data packet traffic(e.g., mobile device movement data) to and from base stations 111 band/or 113 b. Base stations 111 b and 113 b may comprise cellular towersor access points implementing any one or more cellular or mobile devicestandards, including, for example, any of GSM, UMTS, CDMA, NMT, LTE, 5GNR, or the like.

Exemplary Embodiments

The following discussion teaches systems and methods for, inter alia,voice assisted goods delivery. For example, the following discussionteaches how to leverage the example infrastructure of FIG. 1 to providebetter goods delivery to a purchaser of an item.

FIG. 2 shows an overview flowchart of an example implementation. Withreference thereto, at step 210, the merchant 101 defines a set of flows.The flows may be flow processes of an app or website of the merchant101. Example flows include: (i) requesting curbside pickup of an item,(ii) requesting locker storage of the item, (iii) requesting anindication of locations that the item is available, (iv) requesting anindication of an inventory of a retail store, (v) requesting ads for anadditional item that is related to the item, (vi) requesting a status ofan order for the item, (vii) requesting drone delivery of the item froma retail store to a residence, and (viii) requesting drone delivery ofthe item from a warehouse to the residence.

At step 220, the merchant 101 provides the flows to audio analyzingentity 130. At step 230, the audio analyzing entity 130 creates model oralgorithm 138 that analyzes audio data of a user to find an intent ofthe user that maps to one of the defined flows. In some embodiments, themodel or algorithm 138 may be provided to a computing device so that itmay be run as part of the digital assistant 107 to find an intent basedon audio data.

At step 240, the audio analyzing entity 130 receives audio data from auser. The user may send the audio data from any device including asmartphone, tablet, personal computer, car, smart home, smart speaker,or so forth. At step 250, audio analyzing entity 130 analyzes the audiodata with the created model or algorithm (e.g., model 138 of FIG. 1) todetermine an intent of the user. At step 260, the audio analyzing entity130 provides the determined intent to the merchant 101. At step 270, themerchant 101 executes a flow for the user corresponding to thedetermined intent.

Furthermore, although the example of FIG. 2 is illustrated with respectto audio data, it should be understood that any digital data, such astext message data, may be used in addition to or in place of the audiodata.

FIG. 3 shows an example implementation of a process including using adigital assistant 107. With reference thereto, at step 310, digitalassistant 107 is launched on a mobile device, such as mobile device 111m. Although the example of FIG. 1 illustrates the digital assistant 107running on the mobile device 111 m, it should be understood that thedigital assistant 107 may be run on any computing device, such as mobiledevice 113 m, car 150, smart speaker 155, smart home 160, and so forth.At step 320, the digital assistant 107 receives the audio data (e.g., bythe user speaking into the smartphone).

At step 330, the digital assistant 107 determines an intent of the userbased on the received audio data. The digital assistant 107 determinesthe intent based on analyzing words, phrases, sounds, etc. from theaudio data. At step 340, a flow (e.g., a flow process) of app 112 or ofa website maintained by merchant 101 is executed based on the determinedintent. The flow process may be executed by linking or deep linking to aUniform Resource Indicator (URI) or Uniform Resource Locator (URL). Insome embodiments, this is accomplished by defining an Extensible MarkupLanguage (XML) file within the app 112 to map the intent to the URI orURL. The flow may be any of the flows discussed herein.

To further illustrate, in one example of steps 330 and 340, if the usersays, “Hey digital assistant, place order for curbside pickup of itemXYZ at retail location ABC,” the digital assistant 107 may access a flowof a retail app (e.g., app 112) to place the order for curbside pickup(e.g., at retail stores 103 or 180; warehouses 108 or 175; etc.).

The flow process may further involve drone delivery. For example, theremay be a flow for a user to request drone delivery to the user'sresidence, which may result in faster delivery than if other deliverymethods are used. In this example, a drone from drone fleet 170 maydeliver the purchased item from any of retail stores 103, 180, orwarehouses 108, 175 to the user's residence or other requested location.

Another flow process may involve ads for related items. For example, ifa user is shopping online and viewing a product, the user may request toview related items (e.g., request to view ads for related items). Inthis way, the user may find a better deal for a product type, or find aproduct that is more particularly suited to the user's needs.

Moreover, it should be understood that in some embodiments, the app 112does not have access to the audio data, and rather only has access tothe determined intent. In this way, less information is shared, therebyimproving data privacy and security.

At step 350, the digital assistant 107 determines if the user isfinished using the digital assistant 107. If so, the method ends at step360. If not, the method returns to step 320 and additional audio data isreceived.

Furthermore, although the example of FIG. 3 is illustrated with respectto audio data, it should be understood that any digital data, such astext message data, may be used in addition to or in place of the audiodata.

FIG. 4 shows an example implementation of a process, including audiodata being sent to an audio analyzer 130 to determine an intent. Withreference thereto, at step 310, digital assistant 107 is launched on amobile device 310, such as mobile device 111 m. Although the example ofFIG. 1 illustrates the digital assistant 107 running on the mobiledevice 111 m, it should be understood that the digital assistant 107 maybe run on any computing device, such as mobile device 113 m, car 150,smart speaker 155, smart home 160, and so forth. At step 320, thedigital assistant 107 receives the audio data (e.g., by the userspeaking into the smartphone).

At step 410, the digital assistant 107 sends the audio data to the audioanalyzer 130. At step 420, the audio analyzer 130 analyzes the audiodata (e.g., using model 138) to determine an intent. The audio analyzer130 may determine the intent based on analyzing words, phrases, sounds,etc. At step 430, the audio analyzer 130 sends the determined intentback to the digital assistant. In some embodiments, the audio analyzer130 sends only the intent back to the digital assistant, and the audioanalyzer 130 deletes the audio data so that no entity has a copy of theaudio data, thereby improving data privacy and security.

At step 340, a flow process is executed (e.g., by the digital assistant107, app 112, or website of the merchant 101) based on the receivedintent. The flow process may be executed by linking or deep linking to aURI or URL. In some embodiments, this is accomplished by defining an XMLfile within the app 112 to map the intent to the URI or URL. The flowmay be any of the flows discussed herein.

At step 350, the digital assistant 107 determines if the method isfinished. If so, the method ends at step 360. If not, the method returnsto step 320, and additional audio data is sent to the audio analyzer130.

Furthermore, although the example of FIG. 4 is illustrated with respectto audio data, it should be understood that any digital data, such astext message data, may be used in addition to or in place of the audiodata.

Additional Exemplary Embodiments

Aspect 1. In one aspect, there is computer computer-implemented methodfor voice assisted delivery of goods, the method comprising:

determining an intent from digital data, wherein the digital datacomprises audio data or text message data;

matching the determined intent to a flow of a set of flows, wherein theset of flows includes at least one of: (i) requesting curbside pickup ofan item, (ii) requesting locker storage of the item, (iii) requesting anindication of locations that the item is available, (iv) requesting anindication of an inventory of a retail store, (v) requesting ads for anadditional item that is related to the item, (vi) requesting a status ofan order for the item, (vii) requesting drone delivery of the item froma retail store to a residence, or (viii) requesting drone delivery ofthe item from a warehouse to the residence; and

executing the matched flow of the set of flows.

Aspect 2. The computer-implemented method of aspect 1, wherein theexecuting the flow of the set of flows comprises:

using an Extensible Markup Language (XML) file to access a UniformResource Identifier (URI).

Aspect 3. The computer-implemented method of any of aspects 1-2, whereinthe executing the flow of the set of flows comprises:

deep linking to a Uniform Resource Locator (URL).

Aspect 4. The computer-implemented method of any of aspects 1-3, furthercomprising:

receiving, with a digital assistant of a mobile device, the digitaldata; and

wherein the matching the determined intent to a flow of the set of flowsis done by the digital assistant of the mobile device.

Aspect 5. The computer-implemented method of any of aspects 1-4, furthercomprising:

receiving, with a digital assistant of a mobile device, the digitaldata; and

sending the digital data from the digital assistant to an audioanalyzer;

wherein the matching the determined intent to a flow of the set of flowsis done by the digital assistant of the mobile device; and

wherein the method further comprises sending the determined intent fromthe audio analyzer to the digital assistant.

Aspect 6. The computer-implemented method of any of aspects 1-5,wherein:

the intent is determined by a digital assistant that receives thedigital data; and

the digital assistant sends only the determined intent to an app of amerchant, and does not send the digital data to the app of the merchant.

Aspect 7. The computer-implemented method of any of aspects 1-6,wherein:

the intent is determined by an audio analyzer that receives the digitaldata; and

the audio analyzer sends only the determined intent to a merchant, anddoes not send the digital data to the merchant.

Aspect 8. The computer-implemented method of any of aspects 1-7, whereinthe set of flows includes all of: (i) requesting curbside pickup of anitem, (ii) requesting locker storage of the item, (iii) requesting anindication of locations that the item is available, (iv) requesting anindication of an inventory of a retail store, (v) requesting ads for anadditional item that is related to the item, (vi) requesting a status ofan order for the item, (vii) requesting drone delivery of the item froma retail store to a residence, and (viii) requesting drone delivery ofthe item from a warehouse to the residence.

Aspect 9. The computer-implemented method of any of aspects 1-8, whereinthe intent is determined from words or phrases from the digital data.

Aspect 10. A computer system for voice assisted delivery of goods, thecomputer system comprising one or more processors configured to:

determine an intent from digital data, wherein the digital datacomprises audio data or text message data;

match the determined intent to a flow of a set of flows, wherein the setof flows includes locating at least one of: (i) requesting curbsidepickup of an item, (ii) requesting locker storage of the item, (iii)requesting an indication of locations that the item is available, (iv)requesting an indication of an inventory of a retail store, (v)requesting ads for an additional item that is related to the item, (vi)requesting a status of an order for the item, (vii) requesting dronedelivery of the item from a retail store to a residence, or (viii)requesting drone delivery of the item from a warehouse to the residence;and

execute the matched flow of the set of flows.

Aspect 11. The computer system of aspect 10, wherein the one or moreprocessors are further configured to execute the flow of the set offlows by:

using an Extensible Markup Language (XML) file to access a UniformResource Identifier (URI).

Aspect 12. The computer system of any of aspects 10-11, wherein the oneor more processors are further configured to execute the flow of the setof flows by:

deep linking to a Uniform Resource Locator (URL).

Aspect 13. The computer system of any of aspects 10-12, wherein the oneor more processors are further configured to:

receive, with a digital assistant of a mobile device, the digital data;

wherein the matching the determined intent to a flow of the set of flowsis done by the digital assistant of the mobile device.

Aspect 14. The computer system of any of aspects 10-13, wherein the oneor more processors are further configured to:

receive, with a digital assistant of a mobile device, the audio data;and

send the digital data from the digital assistant to an audio analyzer;

receive, with the digital assistant, an intent from the audio analyzer,wherein the intent was determined by the audio analyzer based on theaudio data.

Aspect 15. A computer system for voice assisted delivery of goods,comprising:

one or more processors; and

a program memory coupled to the one or more processors and storingexecutable instructions that, when executed by the one or moreprocessors, cause the computer system to:

determine an intent from audio data;

match the determined intent to a flow of a set of flows, wherein the setof flows includes at least one of: (i) requesting curbside pickup of anitem, (ii) requesting locker storage of the item, (iii) requesting anindication of locations that the item is available, (iv) requesting anindication of an inventory of a retail store, (v) requesting ads for anadditional item that is related to the item, (vi) requesting a status ofan order for the item, (vii) requesting drone delivery of the item froma retail store to a residence, or (viii) requesting drone delivery ofthe item from a warehouse to the residence; and

execute the matched flow of the set of flows.

Aspect 16. computer system of aspect 15, wherein the executableinstructions further cause the computer system to execute the flow ofthe set of flows by:

using an Extensible Markup Language (XML) file to access a UniformResource Identifier (URI).

Aspect 17. The computer system of any of aspects 15-16, wherein theexecutable instructions further cause the computer system to execute theflow of the set of flows by:

deep linking to a Uniform Resource Locator (URL).

Aspect 18. The computer system of any of aspects 15-17, wherein theexecutable instructions further cause the computer system to:

receive, with a digital assistant of a mobile device, the audio data;

wherein the matching the determined intent to a flow of the set of flowsis done by the digital assistant of the mobile device.

Aspect 19. The computer system of any of aspects 15-18, wherein theexecutable instructions further cause the computer system to:

receive, with a digital assistant of a mobile device, the audio data;

send the audio data from the digital assistant to an audio analyzer;

receive, with the digital assistant, an intent from the audio analyzer,wherein the intent was determined by the audio analyzer based on theaudio data.

Aspect 20. The computer system of any of aspects 15-19, wherein the setof flows includes all of: (i) requesting curbside pickup of an item,(ii) requesting locker storage of the item, (iii) requesting anindication of locations that the item is available, (iv) requesting anindication of an inventory of a retail store, (v) requesting ads for anadditional item that is related to the item, (vi) requesting a status ofan order for the item, (vii) requesting drone delivery of the item froma retail store to a residence, and (viii) requesting drone delivery ofthe item from a warehouse to the residence.

Other Matters

Additionally, certain embodiments are described herein as includinglogic or a number of routines, subroutines, applications, orinstructions. These may constitute either software (code embodied on anon-transitory, tangible machine-readable medium) or hardware. Inhardware, the routines, etc., are tangible units capable of performingcertain operations and may be configured or arranged in a certainmanner. In example embodiments, one or more computer systems (e.g., astandalone, client or server computer system) or one or more hardwaremodules of a computer system (e.g., a processor or a group ofprocessors) may be configured by software (e.g., an application orapplication portion) as a hardware module that operates to performcertain operations as described herein.

In various embodiments, a hardware module may be implementedmechanically or electronically. For example, a hardware module maycomprise dedicated circuitry or logic that is permanently configured(e.g., as a special-purpose processor), such as a field programmablegate array (FPGA) or an application-specific integrated circuit (ASIC)to perform certain operations. A hardware module may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that istemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “hardware module” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. Considering embodiments inwhich hardware modules are temporarily configured (e.g., programmed),each of the hardware modules need not be configured or instantiated atany one instance in time. For example, where the hardware modulescomprise a general-purpose processor configured using software, thegeneral-purpose processor may be configured as respective differenthardware modules at different times. Software may accordingly configurea processor, for example, to constitute a particular hardware module atone instance of time and to constitute a different hardware module at adifferent instance of time.

Hardware modules can provide information to, and receive informationfrom, other hardware modules. Accordingly, the described hardwaremodules may be regarded as being communicatively coupled. Where multipleof such hardware modules exist contemporaneously, communications may beachieved through signal transmission (e.g., over appropriate circuitsand buses) that connect the hardware modules. In embodiments in whichmultiple hardware modules are configured or instantiated at differenttimes, communications between such hardware modules may be achieved, forexample, through the storage and retrieval of information in memorystructures to which the multiple hardware modules have access. Forexample, one hardware module may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware module may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware modules may also initiate communications with input oroutput devices, and can operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules.

Similarly, the methods or routines described herein may be at leastpartially processor-implemented. For example, at least some of theoperations of a method may be performed by one or more processors orprocessor-implemented hardware modules. The performance of certain ofthe operations may be distributed among the one or more processors, notonly residing within a single machine, but deployed across a number ofmachines. In some example embodiments, the processor or processors maybe located in a single location (e.g., within a home environment, anoffice environment or as a server farm), while in other embodiments theprocessors may be distributed across a number of geographic locations.

What is claimed:
 1. A computer computer-implemented method for voiceassisted delivery of goods, the method comprising: determining an intentfrom digital data, wherein the digital data comprises audio data or textmessage data; matching the determined intent to a flow of a set offlows, wherein the set of flows includes at least one of: (i) requestingcurbside pickup of an item, (ii) requesting locker storage of the item,(iii) requesting an indication of locations that the item is available,(iv) requesting an indication of an inventory of a retail store, (v)requesting ads for an additional item that is related to the item, (vi)requesting a status of an order for the item, (vii) requesting dronedelivery of the item from a retail store to a residence, or (viii)requesting drone delivery of the item from a warehouse to the residence;and executing the matched flow of the set of flows.
 2. Thecomputer-implemented method of claim 1, wherein the executing the flowof the set of flows comprises: using an Extensible Markup Language (XML)file to access a Uniform Resource Identifier (URI).
 3. Thecomputer-implemented method of claim 1, wherein the executing the flowof the set of flows comprises: deep linking to a Uniform ResourceLocator (URL).
 4. The computer-implemented method of claim 1, furthercomprising: receiving, with a digital assistant of a mobile device, thedigital data; wherein the matching the determined intent to a flow ofthe set of flows is done by the digital assistant of the mobile device.5. The computer-implemented method of claim 1, further comprising:receiving, with a digital assistant of a mobile device, the digitaldata; and sending the digital data from the digital assistant to anaudio analyzer; wherein the matching the determined intent to a flow ofthe set of flows is done by the digital assistant of the mobile device;and wherein the method further comprises sending the determined intentfrom the audio analyzer to the digital assistant.
 6. Thecomputer-implemented method of claim 1, wherein: the intent isdetermined by a digital assistant that receives the digital data; andthe digital assistant sends only the determined intent to an app of amerchant, and does not send the digital data to the app of the merchant.7. The computer-implemented method of claim 1, wherein: the intent isdetermined by an audio analyzer that receives the digital data; and theaudio analyzer sends only the determined intent to a merchant, and doesnot send the digital data to the merchant.
 8. The computer-implementedmethod of claim 1, wherein the set of flows includes all of: (i)requesting curbside pickup of an item, (ii) requesting locker storage ofthe item, (iii) requesting an indication of locations that the item isavailable, (iv) requesting an indication of an inventory of a retailstore, (v) requesting ads for an additional item that is related to theitem, (vi) requesting a status of an order for the item, (vii)requesting drone delivery of the item from a retail store to aresidence, and (viii) requesting drone delivery of the item from awarehouse to the residence.
 9. The computer-implemented method of claim1, wherein the intent is determined from words or phrases from thedigital data.
 10. A computer system for voice assisted delivery ofgoods, the computer system comprising one or more processors configuredto: determine an intent from digital data, wherein the digital datacomprises audio data or text message data; match the determined intentto a flow of a set of flows, wherein the set of flows includes at leastone of: (i) requesting curbside pickup of an item, (ii) requestinglocker storage of the item, (iii) requesting an indication of locationsthat the item is available, (iv) requesting an indication of aninventory of a retail store, (v) requesting ads for an additional itemthat is related to the item, (vi) requesting a status of an order forthe item, (vii) requesting drone delivery of the item from a retailstore to a residence, or (viii) requesting drone delivery of the itemfrom a warehouse to the residence; and execute the matched flow of theset of flows.
 11. The computer system of claim 10, wherein the one ormore processors are further configured to execute the flow of the set offlows by: using an Extensible Markup Language (XML) file to access aUniform Resource Identifier (URI).
 12. The computer system of claim 10,wherein the one or more processors are further configured to execute theflow of the set of flows by: deep linking to a Uniform Resource Locator(URL).
 13. The computer system of claim 10, wherein the one or moreprocessors are further configured to: receive, with a digital assistantof a mobile device, the digital data; wherein the matching thedetermined intent to a flow of the set of flows is done by the digitalassistant of the mobile device.
 14. The computer system of claim 10,wherein the one or more processors are further configured to: receive,with a digital assistant of a mobile device, the digital data; send thedigital data from the digital assistant to an audio analyzer; andreceive, with the digital assistant, an intent from the audio analyzer,wherein the intent was determined by the audio analyzer based on theaudio data.
 15. A computer system for voice assisted delivery of goods,comprising: one or more processors; and a program memory coupled to theone or more processors and storing executable instructions that, whenexecuted by the one or more processors, cause the computer system to:determine an intent from audio data; match the determined intent to aflow of a set of flows, wherein the set of flows includes at least oneof: (i) requesting curbside pickup of an item, (ii) requesting lockerstorage of the item, (iii) requesting an indication of locations thatthe item is available, (iv) requesting an indication of an inventory ofa retail store, (v) requesting ads for an additional item that isrelated to the item, (vi) requesting a status of an order for the item,(vii) requesting drone delivery of the item from a retail store to aresidence, or (viii) requesting drone delivery of the item from awarehouse to the residence; and execute the matched flow of the set offlows.
 16. The computer system of claim 15, wherein the executableinstructions further cause the computer system to execute the flow ofthe set of flows by: using an Extensible Markup Language (XML) file toaccess a Uniform Resource Identifier (URI).
 17. The computer system ofclaim 15, wherein the executable instructions further cause the computersystem to execute the flow of the set of flows by: deep linking to aUniform Resource Locator (URL).
 18. The computer system of claim 15,wherein the executable instructions further cause the computer systemto: receive, with a digital assistant of a mobile device, the audiodata; wherein the matching the determined intent to a flow of the set offlows is done by the digital assistant of the mobile device.
 19. Thecomputer system of claim 15, wherein the executable instructions furthercause the computer system to: receive, with a digital assistant of amobile device, the audio data; and send the audio data from the digitalassistant to an audio analyzer; receive, with the digital assistant, anintent from the audio analyzer, wherein the intent was determined by theaudio analyzer based on the audio data.
 20. The computer system of claim15, wherein the set of flows includes all of: (i) requesting curbsidepickup of an item, (ii) requesting locker storage of the item, (iii)requesting an indication of locations that the item is available, (iv)requesting an indication of an inventory of a retail store, (v)requesting ads for an additional item that is related to the item, (vi)requesting a status of an order for the item, (vii) requesting dronedelivery of the item from a retail store to a residence, and (viii)requesting drone delivery of the item from a warehouse to the residence.